Genes selection from single cell gene expression profiles of melanomas using tensor decomposition based feature extraction
DOI:
https://doi.org/10.51094/jxiv.336Keywords:
machine learning, cancerAbstract
In this work we applied tensor decomposition based feature extraction to gene selection from gene expression profiles of melanomas of single-cell RNA sequencing (scRNA-seq) aiming for a gene set that is expressed without depending on the samples (melanomas). We performed an enrichment analysis of the selected gene set and consequently obtained terms of pathways and Gene Ontology (GO).
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Submitted: 2023-03-21 07:08:39 UTC
Published: 2023-03-23 08:22:36 UTC
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Nobuchika Matsuda
Y-h. Taguchi
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